Cristina Amado
Cristina Amado is assistant professor at the University of Minho, Department of Economics, and a research member of the Economic Policies Research Unit (NIPE). She is an international research fellow at CREATES, Aarhus University.
She holds a PhD in Economic Statistics from the Stockholm School of Economics, June 2009. Her PhD thesis entitled "Four Essays on the Econometric Modelling of Volatility and Durations" focused on topics of modelling financial market volatility and the econometrics of ultra-high-frequency data.
Her main research interests lie within the fields of time series analysis, nonlinear time series modelling and mathematical statistics.
Campos-Martins, S. & Amado, C. (2022). Financial market linkages and the sovereign debt crisis. Journal of International Money and Finance, 123, Article 102596. https://doi.org/10.1016/j.jimonfin.2021.102596
Amado, C., Silvennoinen, A. & Terasvirta, T. (2019). Models with Multiplicative Decomposition of Conditional Variances and Correlations. In J. Chevallier, S. Goutte, D. Guerreiro, S. Saglio & B. Sanjahi (Eds.), Financial Mathematics, Volatility and Covariance Modelling (Vol. 2, pp. 217-260). Routledge.
Amado, C., Silvennoinen, A. & Terasvirta, T. (2017). Modelling and forecasting WIG20 daily returns. Central European Journal of Economic Modelling and Econometrics, 9(3), 173-200. http://cejeme.org/publishedarticles/2017-17-29-636423094307656250-5104.pdf
Amado, C., Silvennoinen, A. & Terasvirta, T. (2017). Modelling and forecasting WIG20 daily returns. (pp. 173-200). Institut for Økonomi, Aarhus Universitet. CREATES Research Paper No. 2017-29
Amado, C. & Teräsvirta, T. (2017). Specification and testing of Multiplicative Time-Varying GARCH models with applications. Econometric Reviews, 36(4), 421-446. Advance online publication. https://doi.org/10.1080/07474938.2014.977064
Amado, C. & Teräsvirta, T. (2014). Conditional correlation models of autoregressive conditional heteroscedasticity with nonstationary GARCH equations. Journal of Business and Economic Statistics, 32(1), 69-87. https://doi.org/10.1080/07350015.2013.847376
Amado, C. & Teräsvirta, T. (2014). Modelling changes in the unconditional variance of long stock return series. Journal of Empirical Finance, 25, 15-35. https://doi.org/10.1016/j.jempfin.2013.09.003
Amado, C. & Laakkonen, H. (2014). Modelling Time-Varying Volatility in Financial Returns: Evidence from the Bond Markets. In N. Haldrup, M. Meitz & P. Saikkonen (Eds.), Essays in Nonlinear Time Series Econometrics Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199679959.003.0006
Amado, C. & Teräsvirta, T. (2013). Modelling volatility by variance decomposition. Journal of Econometrics, 175(2), 142-153. https://doi.org/10.1016/j.jeconom.2013.03.006
